移动P2P文件共享系统中基于用户偏好的激励机制

提出一种基于用户偏好的激励机制,鼓励用户通过提供共享文件和转发操作为系统做出贡献。IMBPC结合了虚拟价格机制和预期文件传输延时,基于用户对价格和延时的偏好度来选择最合适的节点进行文件下载。通过设置模拟实同仅通过虚拟价格机制来激励用户做出贡献的策略进行比较,显示应用IMBPC策略的系统,节点的贡献积极性明显增加。     

Global dynamics for non-autonomous reaction-diffusion neural networks with time-varying delays

In this paper, a class of non-autonomous reaction-diffusion neural networks with time-varying delays is considered. Novel methods to study the global dynamical behavior of these systems are proposed. Employing the properties of diffusion operator and the method of delayed inequalities analysis, we investigate global exponential stability, positive invariant sets and global attracting sets of the neural networks under consideration. Furthermore, conditions sufficient for the existence and uniqueness of periodic attractors for periodic neural networks are derived and the existence range of the attractors is estimated. Finally two examples are given to demonstrate the effectiveness of these results.     

Computing all efficient solutions of the biobjective minimum spanning tree problem

A common way of computing all efficient (Pareto optimal) solutions for a biobjective combinatorial optimisation problem is to compute first the extreme efficient solutions and then the remaining, non-extreme solutions. The second phase, the computation of non-extreme solutions, can be based on a “k-best” algorithm for the single-objective version of the problem or on the branch-and-bound method. A k-best algorithm computes the k-best solutions in order of their objective values. We compare the performance of these two approaches applied to the biobjective minimum spanning tree problem. Our extensive computational experiments indicate the overwhelming superiority of the k-best approach. We propose heuristic enhancements to this approach which further improve its performance.     

Stability of linear multistep methods for delay integro-differential equations

This paper is concerned with the numerical solution of delay integro-differential equations. The adaptation of linear multistep methods is considered. The emphasis is on the linear stability of numerical methods. It is shown that every A-stable, strongly 0-stable linear multistep method of Pouzet type can preserve the delay-independent stability of the underlying linear systems. In addition, some delay-dependent stability conditions for the stability of numerical methods are also given.     

Invariant and attracting sets of impulsive delay difference equations with continuous variables

The aim of this paper is to study the invariant and attracting sets of impulsive delay difference equations with continuous variables. Some criteria for the invariant and attracting sets are obtained by using the decomposition approach and delay difference inequalities with impulsive initial conditions.     

Delay composition in preemptive and non-preemptive real-time pipelines

Uniprocessor schedulability theory made great strides, in part, due to the simplicity of composing the delay of a job from the execution times of higher-priority jobs that preempt it. In this paper, we bound the end-to-end delay of a job in a multistage pipeline as a function of job execution times on different stages under preemptive as well as non-preemptive scheduling. We show that the end-to-end delay is bounded by that of a single virtual “bottleneck” stage plus a small additive component. This contribution effectively transforms the pipeline into a single stage system. The wealth of schedulability analysis techniques derived for uniprocessors can then be applied to decide the schedulability of the pipeline. The transformation does not require imposing artificial per-stage deadlines, but rather models the pipeline as a whole and uses the end-to-end deadlines directly in the single-stage analysis. It also does not make assumptions on job arrival patterns or periodicity and thus can be applied to periodic and aperiodic tasks alike. We show through simulations that this approach outperforms previous pipeline schedulability tests except for very short pipelines or when deadlines are sufficiently large. The reason lies in the way we account for execution overlap among stages. We discuss how previous approaches account for overlap and point out interesting differences that lead to different performance advantages in different cases. Further, we also show that in certain cases non-preemptive scheduling can result in higher system utilization than preemptive scheduling in pipelined systems. We hope that the pipeline delay composition rule, derived in this paper, may be a step towards a general schedulability analysis foundation for large distributed systems.

Evaluation of neural networks-based controllers in batch polymerisation of methyl methacrylate

The importance of batch reactors in today's process industries cannot be overstated. Thus said, it is important to optimise their operation in order to consistently achieve products of high quality while minimising the production of undesirables. In processes like polymerisation, these reactors are responsible for a greater number of products than other reactor types and the need for optimal operation is therefore greater.

An approach based on an offline dynamic optimisation and online control strategy is used in this work to generate optimal set point profiles for the batch polymerisation of methyl methacrylate. Dynamic optimisation is carried out from which controller set points to attain desired polymer molecular end point characteristics are achieved. Temperature is the main variable to be controlled, and this is done over finite discrete intervals of time.

For on-line control, we evaluate the performance of neural networks in two controllers used to track the derived optimal set points for the system. The controllers are generic model control (GMC), ([P.L. Lee, G.R. Sullivan, Generic model control, Comput. Chem. Eng. 12(6) (1998) 573–580]) and the neural network-based inverse model-based control (IMBC), ([M.A. Hussain, L.S. Kershenbaum, Implementation of an inverse model based control strategy using neural networks on a partially simulated exothermic reactor, Trans. IchemE 78(A) (2000) 299–311]). Although the GMC is a model-based controller, neural networks are used to estimate the heat release within its framework for on-line control. Despite the application of these two controllers to general batch reactors, no published work exists on their application to batch polymerisation in the literature. In this work, the performance of the neural networks within each controller's algorithm for tracking and setpoint regulation of the optimal trajectory and in robustness tests on the system is evaluated.     

基于积分二次约束时滞不确定系统的H∞可靠性控制

把基于积分二次约束H∞可靠性控制方法引入状态与时滞不确定系统。通过LMI方法导出无扰动时滞系统具有二次约束H∞可靠性控制的时滞依赖标准,降低有关判定系统鲁棒稳定性条件的保守性。通过推导获得参数与时滞不确定系统的时滞依赖标准。通过数例说明所得结论。     

网络化控制性能与带宽调度协调优化设计及其仿真

基于网络化控制系统是具有延迟约束的实时系统,首先建立了保证网络控制性能的延迟约束模型,以此为基础提出满足上述延迟约束的带宽调度策略,以兼顾控制系统控制性能和网络系统服务质量;利用时间需求分析,给出在该策略下的周期、偶发与非周期等３种网络数据的可调度条件及延迟估计的算法,给出调度策略与保证网络控制性能的协调优化设计方法;最后提出一种控制系统与网络调度的集成仿真平台,并举例说明了策略的有效性．     

运动载体的惯性／天文导航系统仿真研究

对惯性/天文组合导航系统在运动载体上的应用进行了研究.在分析天文导航系统测姿原理的基础上,建立了组合导航系统的数学模型,介绍了一种姿态角误差转换矩阵的求取方式,针对运动载体姿态相对变化较快而存在的输出延迟问题,研究一种在采用卡尔曼滤波进行信息融合过程中,进行延迟误差补偿的数据处理方法.基于建立的数学模型,运用卡尔曼滤波方法对延迟补偿前后的系统进行了仿真比较,仿真结果表明文中所设计算法可以较好地满足运动载体的定姿定位要求.